How AI companies should price

Key Concepts:

• Attribution: The ability to directly link the value provided by a product or service to specific outcomes or KPIs.
• Autonomy: The degree to which a product or service operates independently, without human intervention.
• Pricing Archetypes: Seed-based/Subscription, Hybrid, Pay-for-Consumption, Outcome-Based.

Framework for AI Pricing

The framework presented uses two axes: Attribution (low to high) and Autonomy (low to high) to determine the optimal pricing model for AI-driven products and services.

1. Low Attribution, Low Autonomy (Bottom Left): Seed-Based/Subscription Model

• Characteristics: Inability to directly attribute significant value and lack of autonomous operation (significant human involvement).
• Pricing: Seed-based or subscription model is recommended.
• Rationale: Due to the difficulty in quantifying the value delivered and the reliance on human intervention, a fixed-price model provides predictability for both the provider and the customer.

2. High Attribution, Low Autonomy (Bottom Right): Hybrid Pricing Model

• Characteristics: Strong ability to demonstrate the value delivered (attribution), but still requires human intervention in the process (low autonomy).
• Pricing: Hybrid pricing model is the best option.
• Rationale: The ability to prove attribution allows for a pricing model that reflects the value delivered, while the human element necessitates a model that accounts for the cost of labor or expertise.

3. Low Attribution, High Autonomy (Top Left): Pay-for-Consumption Model

• Characteristics: Highly autonomous operation, but difficulty in directly linking the product's output to specific KPIs or business outcomes (low attribution). Often backend or infrastructure products.
• Pricing: Pay-for-what-you-consume model is necessary.
• Rationale: Since the direct impact on KPIs is unclear, charging based on usage provides a fair and transparent pricing structure.

4. High Attribution, High Autonomy (Top Right): Outcome-Based Pricing Model

• Characteristics: Strong ability to demonstrate the value delivered (attribution) and fully autonomous operation (no human intervention).
• Pricing: Outcome-based pricing model is ideal.
• Rationale: This "magic quadrant" allows for charging based on the value delivered by AI, without the cost of human labor.

Key Argument:

The ultimate goal for AI companies should be to position themselves in the top right quadrant (high attribution, high autonomy) to leverage the full potential of outcome-based pricing. This involves developing AI solutions that can autonomously deliver measurable value to customers.

Conclusion:

The framework provides a strategic guide for determining the optimal pricing model for AI products and services based on their level of autonomy and attribution. The outcome-based pricing model, achievable through high autonomy and high attribution, represents the most advantageous position for AI companies.